On parallel Branch and Bound frameworks for Global Optimization

Branch and Bound (B&B) algorithms are known to exhibit an irregularity of the search tree. Therefore, developing a parallel approach for this kind of algorithms is a challenge. The efficiency of a B&B algorithm depends on the chosen Branching, Bounding, Selection, Rejection, and Termination rules. The question we investigate is how the chosen platform consisting of programming language, used libraries, or skeletons influences programming effort and algorithm performance. Selection rule and data management structures are usually hidden to programmers for frameworks with a high level of abstraction, as well as the load balancing strategy, when the algorithm is run in parallel. We investigate the question by implementing a multidimensional Global Optimization B&B algorithm with the help of three frameworks with a different level of abstraction (from more to less): Bobpp, Threading Building Blocks (TBB), and a customized Pthread implementation. The following has been found. The Bobpp implementation is easy to code, but exhibits the poorest scalability. On the contrast, the TBB and Pthread implementations scale almost linearly on the used platform. The TBB approach shows a slightly better productivity

Blended Learning in Higher Education: Theory and Praxis

Recent studies are showing that ‘blended learning’ is more than a mix between face-to-face and online education, or in other words: a mix of traditional and computer-based education. Blended learning seems to include mixtures between eLearning and other ways of learning, where the right choices have to be made in the distribution of learning content, didactical approaches, ways of communicating and characteristics of learning environments, in the perspective of the type of learning process and characteristics of students. This symposium provides evidence from qualitative studies of blended learning in practical situations, drawing on tutors’ and students’ perspectives, contrasted with theoretical ideas. Attention is focused on assessment in blended learning environments and the use of ePortfolios to align learning, teaching and assessment when new educational approaches are implemented. Also, research on the roles and effectiveness of the eTutor in blended learning will be presented, focussing on academic learning and social integration. Furthermore, attention is focussed on blended strategies in problem-based learning by presenting recent case study research on a postgraduate course for academic staff in ‘eLearning design’. Also, a redesign of the initial teacher training curriculum will be presented, offering different routes for groups of students according to their need of flexibility and support. Finally, a framework is offered for determining the quality of reflection reports in a blended learning environment. In sum, the concept of blended learning is studied from the main perspectives according to learning processes: designing a learning process, supporting a learning process and assessing a learning process. The discussant will go into issues like the design, deliverance, support and evaluation of the presented projects, the degree of internal locus of control for the learners, the assessment methods and tutor and student perceptions on interactions

Blended Learning in Higher Education: Theory and Praxis

Recent studies are showing that ‘blended learning’ is more than a mix between face-to-face and online education, or in other words: a mix of traditional and computer-based education. Blended learning seems to include mixtures between eLearning and other ways of learning, where the right choices have to be made in the distribution of learning content, didactical approaches, ways of communicating and characteristics of learning environments, in the perspective of the type of learning process and characteristics of students. This symposium provides evidence from qualitative studies of blended learning in practical situations, drawing on tutors’ and students’ perspectives, contrasted with theoretical ideas. Attention is focused on assessment in blended learning environments and the use of ePortfolios to align learning, teaching and assessment when new educational approaches are implemented. Also, research on the roles and effectiveness of the eTutor in blended learning will be presented, focussing on academic learning and social integration. Furthermore, attention is focussed on blended strategies in problem-based learning by presenting recent case study research on a postgraduate course for academic staff in ‘eLearning design’. Also, a redesign of the initial teacher training curriculum will be presented, offering different routes for groups of students according to their need of flexibility and support. Finally, a framework is offered for determining the quality of reflection reports in a blended learning environment. In sum, the concept of blended learning is studied from the main perspectives according to learning processes: designing a learning process, supporting a learning process and assessing a learning process. The discussant will go into issues like the design, deliverance, support and evaluation of the presented projects, the degree of internal locus of control for the learners, the assessment methods and tutor and student perceptions on interactions

Self-tuning serverless task farming using proactive elasticity control

The cloud evolved into an attractive execution environment for parallel applications, which make use of compute resources to speed up the computation of large problems in science and industry. Whereas Infrastructure as a Service (IaaS) offerings have been commonly employed, more recently, serverless computing emerged as a novel cloud computing paradigm with the goal of freeing developers from resource management issues. However, as of today, serverless computing platforms are mainly used to process computations triggered by events or user requests that can be executed independently of each other and benefit from on-demand and elastic compute resources as well as per-function billing. In this work, we discuss how to employ serverless computing platforms to operate parallel applications. We specifically focus on the class of parallel task farming applications and introduce a novel approach to free developers from both parallelism and resource management issues. Our approach includes a proactive elasticity controller that adapts the physical parallelism per application run according to user-defined goals. Specifically, we show how to consider a user-defined execution time limit after which the result of the computation needs to be present while minimizing the associated monetary costs. To evaluate our concepts, we present a prototypical elastic parallel system architecture for self-tuning serverless task farming and implement two applications based on our framework. Moreover, we report on performance measurements for both applications as well as the prediction accuracy of the proposed proactive elasticity control mechanism and discuss our key findings